code: def __init__(self, classnames, templates, text_transform):
      self.num_templates = len(templates)
      self.samples = []
      for classname in classnames:
          texts = [template(classname) for template in templates]
          self.samples.extend(text_transform(texts))
  
file_path: NeMo/nemo/collections/multimodal/data/clip/clip_dataset.py
imports: from functools import partial
  from typing import Any, List, Union
  import torch
  from torch.utils.data import Dataset, default_collate
  from nemo.collections.multimodal.data.clip.augmentations.augmentations import image_transform
  from nemo.collections.multimodal.data.clip.imagenet_zeroshot_data import imagenet_classnames, openai_imagenet_template
  from nemo.collections.multimodal.data.common.webdataset import WebDatasetCommon
  from nemo.collections.nlp.data.language_modeling.megatron.data_samplers import MegatronPretrainingSampler
  from nemo.collections.vision.data.megatron.image_folder import ImageFolder
label_desc: Use image node_id 1 to create a new ImagenetClassnameDataset object from inherited base classes: Dataset with example: obj = ImagenetClassnameDataset(classnames, templates, text_transform)